Welcome to the 23rd installment of our blog series “My Path to Google.” These are real stories from Googlers, interns, and alumni highlighting how they got to Google, what their roles are like, and even some tips on how to prepare for interviews.

Today’s post is all about Annie Jean-Baptiste. Read on!

Can you tell us a bit about yourself?
I am a Boston native, and went to school at the University of Pennsylvania, studying International Relations and Political Science. I love New England sports teams, my dog (who comes to work most days), travel (I speak five languages and was a nanny before working at Google), music (I play the cello), and dance (I have danced many genres all my life and most recently danced half-time at college basketball games).

I'm passionate about healthy practices for underrepresented communities and use my platform as an American Heart Association Spokesperson and One Young World ambassador to ensure equal access to resources for communities of color. I think my degree was actually very helpful for my roles at Google—multidisciplinary, global in nature—it taught me to seek out, value, and elevate different perspectives.

What’s your role at Google?
I am the Global Product Inclusion Evangelist for Google. I help ensure we build products for everyone, with everyone. I most recently worked on several projects for Black History Month, including a Google Docs easter egg, where if you typed in #blackhistorymonth and clicked on the explorer box, you got awesome content about black history! What I like most about my role is that I can fuse my background (I started in our Global Business Organization as an Account Manager) with my passion (inclusive products and services).Complete the following: "I [choose one: code/create/design/build] for..."
I build for communities that typically have not had their voices at the forefront, but are brilliant, innovative, and changing the world!What inspires you to come in every day?
I am constantly inspired by Googlers and their commitment to dreaming big and creating a world where everyone—no matter their background—can see themselves in our products and use technology to create a better world.

Can you tell us about your decision to enter the process?
My brother was actually a BOLD intern and encouraged me to apply. I was a senior in college and didn't think Google was for me, given my non-tech background, but I deeply believed in making information universally accessible and useful. I was worried about not fitting in or getting the job, so I was so excited to get it AND be able to move back to the Cambridge office to be close to my family. I stayed in that office for four years, and it's still my favorite office to date!How did the recruitment process go for you?
I applied directly and Google came to my university. I remember how friendly my recruiter was (fun fact: he had been a recruiter previously at my high school), and I also very much appreciated starting with a cohort of new grads—it made the process super fun.

What do you wish you’d known when you started the process?
That there are so many roles at Google—you don't have to be an engineer or a certain type of person to work here. In fact, my team's mission is to make sure that there are diverse perspectives, so we can build products for everyone.Can you tell us about the resources you used to prepare for your interview or role?
For the interview, do your research—keep up with current events, what's going on in the tech industry, etc. Have a position on what excites and intrigues or challenges you in the tech landscape. Think of questions for your interviewer as well—it needs to be a fit for you, too!

Do you have any tips you’d like to share with aspiring Googlers?
Have a deep commitment to always learning. Ask questions. Be humble. Think about those voices you typically don't hear and how to ensure they have a seat at the table.

Welcome to the 22nd installment of our blog series “My Path to Google.” These are real stories from Googlers, interns, and alumni highlighting how they got to Google, what their roles are like, and even some tips on how to prepare for interviews.

Today’s post is all about Christof Leng. Read on!

Can you tell us a bit about yourself?
I was born and raised in Germany, near Frankfurt. I first got in touch with computers as an elementary school kid when my cousin introduced me to video games on his Commodore 64 and showed me how to write simple BASIC programs. The power to teach a machine anything I could imagine, seemed like magic to me (and still does).

Many years later, I received a PhD in computer science from TU Darmstadt on the topic of stochastic replication mechanisms in unstructured peer-to-peer networks. After my PhD, I've been a visiting postdoc at UC Berkeley, working with the AMP Lab folks on Apache Spark.

The developer tools at Google keep amazing me and it's an honor to be in charge of keeping them up and running. As a SRE, I thrive in ambiguity. We don't do the same manual tasks over and over again, like a classic operations role, but implement automation or redesign the system to fix the problem for good. That way, we have the time to pick up new interesting challenges every day. With our daily tasks changing all the time, SRE as an organization evolves at a breathtaking rate.

What inspires you to come in every day?
First and foremost, the fantastic colleagues I get to work with. Secondly, the great work environment Google provides, both the infrastructure and the organizational framework that gives us the freedom to do the right thing.

The scale at which Google operates is simply mind-blowing. You can fire up thousands of servers with the press of a button. You see petabytes of data flying by. And you know that you provide the infrastructure for products used by billions of people around the globe, making things possible everyday that I couldn't even dream of when I was a kid.

Can you tell us about your decision to enter the process?
Google was never an option for me. Even though one of my mentors at grad school moved on to become a manager at Google, I never applied myself. I heard the interviews are terribly hard and imagined I had to move to California, which seemed very far away at the time. My dream was to become a professor, not to work for a large corporation.

Coincidentally, I eventually ended up in Berkeley, California and was approached by a Google recruiter. I guess my LinkedIn profile said something about "big data." They asked, "Have you considered becoming an SRE?" and I was like, "What is that?" I think they had to explain the role to me three times during the interview process (and I still didn't get it). In hindsight, I'm extremely grateful that my academic career didn't pan out. Most stuff at Google is so much more advanced than what I would have been working on in academia.

How did the recruitment process go for you?
I was approached by a recruiter. I was surprised and excited. I also had no idea how to get through the process. Most job interviews in Germany are quite different than the Google process. I got myself two books and gave it a shot. The interviews were as tough as expected, but never unfair. I thought I got lucky with the questions I got, but thought I bombed one session. I think it was the most thorough screening of my technical skills I've ever been through. My recruiter was always very supportive and explained the process to me.What do you wish you’d known when you started the process?
Probably how to negotiate an (even) better salary — I still have no clue how that is done. One thing I'm *glad* I didn't know is how much I would like my job. I would've been much more nervous and probably screwed up in the interviews.

Can you tell us about the resources you used to prepare for your interview or role?The Google Resume and Cracking the Coding Interview by Gayle Laakmann McDowell. Sending my resume to a number of friends and colleagues for advice and proofreading.

Do you have any tips you’d like to share with aspiring Googlers?
Follow your dreams. Always challenge the status quo. But be pragmatic. It's not helping anyone if you have your head in the clouds, but don't deliver results, no matter how little they may seem. One step at a time. Be open to change, especially if it scares you. I regret my failures much less than the risks I didn't dare to take at the time.

Google Research tackles the most challenging problems in CS and related fields. Being bold and taking risks is essential to what we do, and research teams are embedded throughout Google, allowing our discoveries to affect billions of users each day.

The compelling benefit to researchers is that their innovations can be implemented fast and big. Google’s unique infrastructure facilitates ideas’ speed to market — allowing their ideas to be trialled by millions of users before their paper is even published.

Can you tell us about yourself and your masters topic?
I’m a masters student at Stanford University, where I’m a part of the Computational Vision and Geometry Lab — I actually just joined this October, and I’m working on projects related to semantic segmentation. I also studied at Stanford as an undergrad, and previously I worked under Sebastian Thrun with Andre Esteva and Brett Kuprel on deep learning for skin cancer detection. So I work on a lot of vision projects, and I’m especially interested in projects that lie at the intersection of machine learning and healthcare. I’m also really interested in human cognition! I loved reading books by Oliver Sacks and other neuroscientists as a kid, but when I first started in computer science, I never considered that there would be much of a direct overlap where I’d get to actually mess around in both fields. Within artificial intelligence research, though, it seems like we still have a lot to learn from actual human brains.

How did you get to work in this area?
There’s this class at Stanford, CS231N, on deep learning for computer vision. On the very first day, I remember that the professor who co-taught the class — Dr. Fei Fei Li — went through this presentation, and one of the slides was about how the initial layers of convolutional neural networks learn basic edge detecting filters that actually closely parallel the basic edge detectors found in cat and human visual cortices, suggesting that there was a deeper and more fundamental connection between these two vision systems. I thought that was insane, and also insanely cool. I joined Sebastian Thrun’s lab a little later, and have been working on AI research since then.

Why did you apply for an internship at Google and how supportive was your masters advisor?
I’d heard really great things about research at Google, and even in my classes and labs, read lots of very impressive work coming from teams in Mountain View, London, and Zurich. I was hoping to get a better sense of what research looks like outside of an academic setting, and the scope of projects and expertise was a huge draw. Also, zillions of GPUs.

My master’s advisor at Stanford is Dan Jurafsky, who is the man. He’s a computer scientist and linguist, has written a book about the language of food, and is basically the best, as far as I’m concerned. He was super supportive.What project was your internship focused on?
I worked under Andrea Gesmundo from the Applied Machine Intelligence team on Multitask Neural Model Search, a framework to automate deep learning architecture design using reinforcement learning. This work builds off of the Neural Architecture Search research done by Barrett and Quoc from the Google Brain team - that framework was one of the first to successfully apply reinforcement learning to automatically generate convolutional neural networks.

Our project focused on extending that framework so that we could automatically design architectures for multiple different tasks, simultaneously. For example, the same framework could design a model that worked well for sentiment analysis tasks, and another that worked well for language identification, at the same time.

We then showed that it was possible to transfer that framework, so that knowledge learned from designing architectures for previous tasks could be reused in totally new, unseen settings. When actual humans design machine learning models, we don’t start completely from scratch every time — we can take advantage of general intuitive design patterns we’ve observed before, as well as remember what models did and didn’t work on similar tasks in the past — and this research tries to take a step closer to doing the same thing in our automated model design.

Did you publish at Google during your internship?
Yes! We submitted our work to ICML, where it’s currently under review (so fingers crossed). The pre-print is also up on Arxiv.

How closely connected was the work you did during your internship to your masters topic?
Although Andrea and I discussed a bunch of project ideas in the months before the internship, this project was actually a chance to try something fairly different from my master’s research at Stanford. For me, at least, that turned out to be one of the best things about this internship — I really loved the chance to explore a very different aspect of AI research, especially one that benefited from the guidance and computational resources available within Google, and I left with a much deeper interest in reinforcement learning that I’ve continued to explore back at Stanford.

Did you write your own code?
Heck, yeah! And then I deployed it cavalierly with enormous care across tons of GPUs. One really awesome thing about interning, though, is the chance to build off of the collaborative engineering effort of other incredibly talented engineers and researchers. I worked pretty closely with code that was being updated almost daily by researchers on the Brain team over in Mountain View, and that kind of cross-continental engineering work feels really neat.

This is your third internship at Google. What were the reasons to come back to Google Zurich?
Third time’s the charm? But actually, I’ve been lucky enough to work at a different office, on very different projects, during all three internships at Google — after my freshman year, I worked with the Glass team in Mountain View, and later I worked in New York on Google Classroom. Each time, I left with a much deeper understanding and appreciation for that particular field, and the care and expertise each of those teams brought to those particular domains. This summer, though, I wanted to come back to work on research in particular. Both of my previous internships had been very software engineering focused, and I was excited to work on AI research that more closely parallels the work I’m excited about at Stanford.

Also, Zurich! I’ve never been to Switzerland before, and this summer, one of my fellow interns and I took a train out to hike past the Matterhorn. She wisely remembered to bring along a Toblerone bar for comparison. The real thing is much more breathtaking (but a lot less chocolatey.)

[Editor’s note: the photo referenced is the photo at the beginning of this post!]

What key skills have you gained from your time at Google?
My team held a weekly reading group, where we’d gather to read and discuss cutting-edge AI papers chosen by different members of the team. This turned out to be one of the very best experiences of the internship — it was incredibly helpful to step back and get a better sense of what’s happening within a very rapidly changing field. Listening to colleagues step through these papers helped me learn to more rigorously assess any given paper — to ask what the experiments really mean, and how its conclusions could generalize to our own current and future projects. Those are questions that I’ve tried to ask more about any work since the summer. That commitment to keeping up with the very coolest things happening within the field also just serves to remind me, often, of what exactly I love about this work and how much there is left to tackle.

What impact has this internship experience had on your master's?
A ton. I really enjoyed diving deeply into research that was largely outside of my own master’s expertise. So much is changing within reinforcement learning right now, and I’ve definitely brought back what I learned — and a sparked interest in related work — to my research here.

Looking back on your experiences now: Why should a master's student apply for an internship at Google? Any advice to offer?
There’s a kind of magical combination of people and resources that means you can work and learn so much within so short a time — especially if you love research and haven’t yet done a PhD, like myself. The internship offers that same rigor and breadth of very cool projects in a very compressed package.

When you’re here, definitely ask questions. Talk to other people about their research, because it’s going to be very awesome and maybe even directly relevant. Join a reading group. Or start a reading group. And get someone to show you how to actually use the espresso machines. That milk frothy thingie? Life changing.

Registration for Kickstart and Code Jam is open! These two programming competitions are designed for programmers of all levels looking to put their coding skills to the test. All of the problems are designed by a team of Google Engineers to inspire and challenge participants. People from across the globe are invited to join the fun! We have a community of current competitors, former participants, and fans of the competitions across Twitter, YouTube, Google+, and Facebook.

Here’s everything you need to know about Kickstart and Code Jam:

Kickstart: Want to grow your coding skills?

Throughout the year, Code Jam hosts online Kickstart rounds that give participants the opportunity to grow their coding abilities, while getting a glimpse into the programming skills needed for a technical career at Google. There are 8 rounds held throughout the year, and you can participate in one or join them all! Check out a recent YouTube Live where Google engineers walk through tips on how to solve Kickstart problems. If you want to practice before the official rounds, check out previous problems from the competition and try them out for yourself.

Code Jam is Google’s longest-running, global programming competition. Join programmers around the world to challenge yourself, test your coding skills, and practice in a fast-paced environment. The top 1,000 contestants receive limited edition t-shirts featuring code from the previous year’s competition. The top 25 finalists will head to Google's office in Toronto, Canada to attend the World Finals where they'll compete for a cash prize of up to $15,000. We'll livestream the whole event for fans to join in the action! If you want to begin practicing, get started by working your way through previous problems, and join us for a practice session beginning March 23rd at 18:00 UTC.

In honor of Black History Month, Google hosts its annual Pay It Forward Challenge as a way to recognize individuals who are making a positive impact in their communities. The variety of submissions we received this year serves as a reminder that there are so many ways in which students can “pay it forward!” We’re excited to share the work of the students below, and hope that you feel inspired by the different ways in which students across the U.S. are expanding access and opportunities for their local communities!

Digital Initiatives
Individuals are increasingly moving to digital initiatives in order to make a positive impact and reach a large audience. Check out how these students are navigating the digital space in order to ignite change in their communities.

Tim Salau is a current Master’s student in his final year at the University of Texas at Austin studying Information Studies. He is a former Google design intern and creator of the Mentors & Mentees community, an international community centered on career mentorship and personal development. They’ve held webinar and workshops around topics like leadership, how to effectively use LinkedIn, and networking!

Jehron Petty

Jehron Petty, a sophomore at Cornell University, is the co-creator of Minority Wealth Management, a YouTube series which seeks to raise awareness of wealth creation and preservation in the minority community through educational videos and social commentary.

Defining Your Community
There is no one correct definition of “community.” From Ghana to Mississippi, these students scaled their initiatives in order to impact the communities that they felt closest to.

Cynoc Bediako

Cynoc is sophomore at Cornell University studying Computer Science. He was born and raised in Ghana, and he has a passion to make Africa a better place through computer science and technology. As such, earlier this year he organized a hackathon in Kumasi Ghana called “Ghana Hacks.” The program sought to give science students a window into the world of computer science and its vast potential for development in this era of technology.

Aisha Saffold

Aisha Saffold is a native of Lexington, Mississippi, attending Jackson State University. She founded P.E.A.R.L.S. in order to empower young women in Holmes, Rankin, Hinds, Leflore, and the Grenada Counties in Mississippi (close to home). The P.E.A.R.L.S. Leadership Academy, Poise and Etiquette Training, and Get Fit with P.E.A.R.L.S. programs are all examples of ways in which Aisha seeks to mold young girls into role models and powerful women who achieve their own hopes and dreams.

University Initiatives
Busy college students can find ways to impact their local communities by engaging in initiatives with their universities.

Pearis Bellamy

Pearis Bellamy is a senior Psychology major and Leadership Studies minor at Hampton University. She founded the Black College Business Woman Connection as an effort to promote entrepreneurship and community among women. Participants leave the events not only informed and empowered, but with a tribe of women ready to support them!

Taylor Montgomery

Taylor Montgomery is a junior Physics major at Fisk University in Nashville, Tennessee, and only the second African-American young woman to be the Team Lead for the Fisk University Rocket Team. With the Rocket Team, Taylor volunteers to educate underrepresented minority students in the Nashville Metro Public Schools by engaging them in rocketry, robotics, and STEM activities.

Google Initiatives
There are several ways in which you can leverage Google’s programs and resources in order to positively impact your communities!

Koko Lawson

Koko Lawson is pursuing a MBA at Emporia State University. She is a Community Impact Lead for Google Fiber in Kansas City, Missouri, where she works to close the digital divide in the area by providing community organizations with tools and resources to improve the digital literacy of Kansas City.

Welcome to the 21st installment of our blog series “My Path to Google.” These are real stories from Googlers, interns, and alumni highlighting how they got to Google, what their roles are like, and even some tips on how to prepare for interviews.

Today’s post is all about Anjali Khetan. Read on!

Can you tell us a bit about yourself?
I grew up in Stamford, CT, before attending college at the University of Pennsylvania. I spent the first two years studying Chemical Engineering, but after Intro to Computer Science (CS), my heart was forever changed, and I transferred to Computer Science!

What’s your role at Google?
I am a Software Engineer (SWE) on Google Maps. My team works on getting live events on the map all over the world! I love our team, because we strive to organize event data and understand how it relates to maps, places, people, and navigation. This means our work fits in with Google’s overall mission, but it also brings delight to users through fun features like drawing rainbow routes for Pride and other events, and showing them cool things to do in their area.

What inspires you to come in every day?
The people! I love our product and the projects we work on, but my colleagues are far and away the best part—I have never worked with or met such an inspiring and fun group of people.

Can you tell us about your decision to enter the process?
This was my third time applying. It's always worth the energy and effort to chase your dreams, but definitely not a smooth road :D. I joined Google right after college.

How did the recruitment process go for you?
I was contacted after being rejected for an internship. Although I had applied for the SWE New Graduate role, the recruiter felt that I would be a great match for the Engineering Residency program, so we went forward with that.

What do you wish you’d known when you started the process?
That showing an interviewer *how* you solve a problem is just as valuable as what your solution is.

Can you tell us more about the resources you used to prep?
I used “Cracking the Coding Interview,” HackerRank, and mock interviews with friends.

To finish, do you have any tips you’d like to share with aspiring Googlers?
When you love something, the work is easy!